{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simulating Energy Price with 10 paths...\n",
      "Running traditional method...\n",
      "Traditional method completed in 0.89s\n",
      "Running GMT-II method...\n",
      "GMT-II progress: 1/10 paths\n",
      "GMT-II progress: 2/10 paths\n",
      "GMT-II progress: 3/10 paths\n",
      "GMT-II progress: 4/10 paths\n",
      "GMT-II progress: 5/10 paths\n",
      "GMT-II progress: 6/10 paths\n",
      "GMT-II progress: 7/10 paths\n",
      "GMT-II progress: 8/10 paths\n",
      "GMT-II progress: 9/10 paths\n",
      "GMT-II progress: 10/10 paths\n",
      "GMT-II method completed in 0.16s\n",
      "\n",
      "Demonstrating GMT-II Flexibility: Adding Seasonality and Spikes\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x864 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy.stats import norm\n",
    "import time\n",
    "import matplotlib.gridspec as gridspec\n",
    "from fbm import FBM  # 需要安装：pip install fbm\n",
    "\n",
    "# 设置全局样式（避免中文乱码）\n",
    "plt.style.use('seaborn-whitegrid')\n",
    "plt.rcParams.update({\n",
    "    'font.family': 'DejaVu Sans',\n",
    "    'font.size': 10,\n",
    "    'axes.titlesize': 12,\n",
    "    'axes.titleweight': 'bold',\n",
    "    'axes.labelsize': 11,\n",
    "    'lines.linewidth': 1.8,\n",
    "    'legend.fontsize': 9,\n",
    "    'axes.unicode_minus': False\n",
    "})\n",
    "\n",
    "# 电力价格模型参数\n",
    "P0 = 50.0        # 初始电价\n",
    "mu = 50.0        # 长期均衡电价\n",
    "kappa = 1.5      # 均值回复速率\n",
    "sigma = 5.0      # 波动率\n",
    "H = 0.7          # 赫斯特指数（H>0.5表示长记忆）\n",
    "T = 2.0          # 模拟时长（年）\n",
    "dt = 1/252       # 时间步长（交易日）\n",
    "n_steps = int(T/dt)\n",
    "n_paths = 10     # 路径数量\n",
    "\n",
    "# 理论值计算\n",
    "theoretical_var = (sigma**2 * (dt**(2*H)) * (T**(2-2*H))) / (2*H*(2*H-1))\n",
    "\n",
    "# ========================================\n",
    "# 传统SIE求解方法 - 电力价格长程依赖模型\n",
    "# ========================================\n",
    "def traditional_energy_price(P0, mu, kappa, sigma, H, T, dt, n_paths):\n",
    "    n_steps = int(T/dt)\n",
    "    paths = np.zeros((n_steps+1, n_paths))\n",
    "    paths[0, :] = P0\n",
    "    \n",
    "    # 生成分数布朗运动路径\n",
    "    fbm_paths = []\n",
    "    for i in range(n_paths):\n",
    "        fbm = FBM(n=n_steps, hurst=H, length=T)\n",
    "        fbm_path = fbm.fbm()\n",
    "        fbm_paths.append(fbm_path)\n",
    "    \n",
    "    fbm_paths = np.array(fbm_paths).T  # 转置为(time, path)\n",
    "    \n",
    "    # 计算权重核函数 (t-s)^{H-1/2}\n",
    "    ts = np.arange(0, n_steps+1) * dt\n",
    "    kernel = np.zeros(n_steps+1)\n",
    "    for i in range(1, n_steps+1):\n",
    "        kernel[i] = (ts[i])**(H-0.5)\n",
    "    \n",
    "    # 模拟路径\n",
    "    for i in range(1, n_steps+1):\n",
    "        # 均值回复部分\n",
    "        mean_reversion = kappa * (mu - paths[i-1, :]) * dt\n",
    "        \n",
    "        # 分数积分部分 (使用离散卷积)\n",
    "        stochastic_part = np.zeros(n_paths)\n",
    "        for j in range(1, i+1):\n",
    "            weight = kernel[i-j+1] - kernel[i-j] if i-j > 0 else kernel[1]\n",
    "            stochastic_part += weight * (fbm_paths[j, :] - fbm_paths[j-1, :])\n",
    "        \n",
    "        paths[i, :] = paths[i-1, :] + mean_reversion + sigma * stochastic_part\n",
    "        \n",
    "    return paths.T  # 转换为(path, time)\n",
    "\n",
    "# ========================================\n",
    "# 广义映射理论实现 (GMT-II)\n",
    "# ========================================\n",
    "class GeneralizedMappingEnergyPrice:\n",
    "    def __init__(self, P0, mu, kappa, sigma, H, T, dt):\n",
    "        self.P = P0\n",
    "        self.mu = mu\n",
    "        self.kappa = kappa\n",
    "        self.sigma = sigma\n",
    "        self.H = H\n",
    "        self.path = [P0]\n",
    "        self.operations = []\n",
    "        self.n_steps = int(T / dt)\n",
    "        self.fbm = FBM(n=self.n_steps, hurst=H, length=T)\n",
    "        self.fbm_path = self.fbm.fbm()  # 分数布朗运动路径\n",
    "        self.time_step = 0\n",
    "        self.integral = 0.0\n",
    "        \n",
    "    def mean_revert_op(self, dt):\n",
    "        \"\"\"均值回复操作\"\"\"\n",
    "        return self.kappa * (self.mu - self.P) * dt\n",
    "    \n",
    "    def fbm_integral_op(self, dt):\n",
    "        \"\"\"分数布朗运动积分操作\"\"\"\n",
    "        current_time = (self.time_step + 1) * dt\n",
    "        \n",
    "        # 离散积分权重\n",
    "        if self.time_step == 0:\n",
    "            weight = dt**(self.H-0.5)\n",
    "        else:\n",
    "            weight = (current_time)**(self.H-0.5) - (current_time - dt)**(self.H-0.5)\n",
    "        \n",
    "        # 分数布朗运动增量，防止索引越界\n",
    "        if self.time_step + 1 < len(self.fbm_path):\n",
    "            fbm_inc = self.fbm_path[self.time_step+1] - self.fbm_path[self.time_step]\n",
    "        else:\n",
    "            fbm_inc = 0.0\n",
    "        \n",
    "        # 更新积分\n",
    "        self.integral += weight * fbm_inc\n",
    "        \n",
    "        return self.sigma * self.integral\n",
    "    \n",
    "    def step(self, dt):\n",
    "        \"\"\"执行一步GMT操作\"\"\"\n",
    "        if self.time_step >= self.n_steps:\n",
    "            return self.P\n",
    "            \n",
    "        self.time_step += 1\n",
    "        \n",
    "        # 执行操作\n",
    "        mean_rev = self.mean_revert_op(dt)\n",
    "        fbm_int = self.fbm_integral_op(dt)\n",
    "        \n",
    "        # 总变化\n",
    "        total_change = mean_rev + fbm_int\n",
    "        \n",
    "        # 记录操作细节\n",
    "        self.operations.append({\n",
    "            'time': self.time_step * dt,\n",
    "            'mean_reversion': mean_rev,\n",
    "            'fbm_integral': fbm_int,\n",
    "            'total_change': total_change,\n",
    "            'fbm_value': self.fbm_path[self.time_step] if self.time_step < len(self.fbm_path) else 0.0\n",
    "        })\n",
    "        \n",
    "        # 更新状态\n",
    "        self.P += total_change\n",
    "        self.path.append(self.P)\n",
    "        \n",
    "        return self.P\n",
    "    \n",
    "    def simulate(self, T, dt):\n",
    "        \"\"\"完整模拟路径\"\"\"\n",
    "        for i in range(self.n_steps):\n",
    "            self.step(dt)\n",
    "        return self.path, self.operations\n",
    "\n",
    "# ========================================\n",
    "# 执行模拟\n",
    "# ========================================\n",
    "print(f\"Simulating Energy Price with {n_paths} paths...\")\n",
    "\n",
    "# 传统方法\n",
    "print(\"Running traditional method...\")\n",
    "start_time = time.time()\n",
    "trad_energy_paths = traditional_energy_price(P0, mu, kappa, sigma, H, T, dt, n_paths)\n",
    "trad_time = time.time() - start_time\n",
    "print(f\"Traditional method completed in {trad_time:.2f}s\")\n",
    "\n",
    "# GMT-II方法\n",
    "print(\"Running GMT-II method...\")\n",
    "start_time = time.time()\n",
    "gmt_energy_models = []\n",
    "gmt_energy_paths = []\n",
    "\n",
    "for i in range(n_paths):\n",
    "    model = GeneralizedMappingEnergyPrice(P0, mu, kappa, sigma, H, T, dt)\n",
    "    path, _ = model.simulate(T, dt)\n",
    "    gmt_energy_paths.append(path)\n",
    "    gmt_energy_models.append(model)\n",
    "    print(f\"GMT-II progress: {i+1}/{n_paths} paths\")\n",
    "\n",
    "gmt_time = time.time() - start_time\n",
    "print(f\"GMT-II method completed in {gmt_time:.2f}s\")\n",
    "\n",
    "# 时间轴\n",
    "time_axis = np.linspace(0, T, n_steps+1)\n",
    "\n",
    "# ========================================\n",
    "# 结果可视化 (四图布局)\n",
    "# ========================================\n",
    "fig = plt.figure(figsize=(15, 12))\n",
    "gs = gridspec.GridSpec(3, 2, height_ratios=[1.2, 1, 1])\n",
    "\n",
    "# 1. 路径对比图 (左上)\n",
    "ax1 = plt.subplot(gs[0, :])\n",
    "for i in range(min(2, n_paths)):  # 展示两条路径\n",
    "    # 传统方法路径\n",
    "    ax1.plot(time_axis, trad_energy_paths[i], '--', color='royalblue', alpha=0.8,\n",
    "             label=f'Traditional Path {i+1}' if i == 0 else \"\")\n",
    "    \n",
    "    # GMT-II方法路径\n",
    "    ax1.plot(time_axis, gmt_energy_paths[i], '-', color='darkorange', linewidth=1.8,\n",
    "             label=f'GMT-II Path {i+1}' if i == 0 else \"\")\n",
    "\n",
    "ax1.axhline(mu, color='k', linestyle='--', alpha=0.7, label='Equilibrium Price')\n",
    "\n",
    "ax1.set_title('Energy Price Paths with Long Memory: Traditional vs GMT-II', fontsize=12, fontweight='bold')\n",
    "ax1.set_xlabel('Time (Years)', fontsize=11)\n",
    "ax1.set_ylabel('Price', fontsize=11)\n",
    "ax1.legend(fontsize=9, loc='upper left')\n",
    "ax1.grid(True, alpha=0.3)\n",
    "\n",
    "# 2. 分数布朗运动路径 (右上)\n",
    "ax2 = plt.subplot(gs[1, 0])\n",
    "if len(gmt_energy_models) > 0:\n",
    "    model = gmt_energy_models[0]\n",
    "    valid_ops = [op for op in model.operations if op['time'] <= T]\n",
    "    fbm_values = [op['fbm_value'] for op in valid_ops]\n",
    "    fbm_times = [op['time'] for op in valid_ops]\n",
    "    \n",
    "    ax2.plot(fbm_times, fbm_values, 'g-', linewidth=1.8, label='Fractional Brownian Motion')\n",
    "    \n",
    "    # 计算Hurst指数特征\n",
    "    if len(fbm_values) > 10:\n",
    "        log_increments = []\n",
    "        log_scales = []\n",
    "        for scale in [10, 30, 100]:\n",
    "            if len(fbm_values) > scale:\n",
    "                increments = np.diff(fbm_values[::scale])\n",
    "                var = np.var(increments)\n",
    "                log_increments.append(np.log(var))\n",
    "                log_scales.append(np.log(scale))\n",
    "        \n",
    "        # 计算赫斯特指数\n",
    "        if len(log_increments) > 1:\n",
    "            hurst_est = np.polyfit(log_scales, log_increments, 1)[0] / 2\n",
    "            ax2.text(0.05, 0.9, f'Estimated H: {hurst_est:.3f}\\nTheoretical H: {H:.3f}', \n",
    "                     transform=ax2.transAxes, fontsize=9, \n",
    "                     bbox=dict(facecolor='white', alpha=0.7))\n",
    "\n",
    "ax2.set_title('Fractional Brownian Motion Path (Hurst Process)', fontsize=12, fontweight='bold')\n",
    "ax2.set_xlabel('Time (Years)', fontsize=11)\n",
    "ax2.set_ylabel('fBm Value', fontsize=11)\n",
    "ax2.legend(fontsize=9)\n",
    "ax2.grid(True, alpha=0.3)\n",
    "\n",
    "# 3. GMT-II操作分解 (左下)\n",
    "ax3 = plt.subplot(gs[1, 1])\n",
    "if len(gmt_energy_models) > 0:\n",
    "    model = gmt_energy_models[0]  # 第一条路径\n",
    "    valid_ops = [op for op in model.operations if op['time'] <= T]\n",
    "    \n",
    "    # 获取累积贡献\n",
    "    cum_mean_rev = np.cumsum([op['mean_reversion'] for op in valid_ops]) + P0\n",
    "    cum_fbm_int = np.cumsum([op['fbm_integral'] for op in valid_ops]) + P0\n",
    "    total_path = [P0] + [P0 + sum(op['mean_reversion'] + op['fbm_integral'] \n",
    "                                 for op in valid_ops[:i]) for i in range(1, len(valid_ops)+1)]\n",
    "    \n",
    "    # 时间点\n",
    "    times = [op['time'] for op in valid_ops]\n",
    "    \n",
    "    # 可视化分解\n",
    "    plt.plot(times, cum_mean_rev, 'b-', label='Cumulative Mean Reversion', linewidth=1.8)\n",
    "    plt.plot(times, cum_fbm_int, 'm-', label='Cumulative fBm Integral', linewidth=1.8)\n",
    "    plt.plot(time_axis, model.path[:len(time_axis)], 'k-', alpha=0.7, label='Total Price Path', linewidth=1.8)\n",
    "    plt.axhline(mu, color='k', linestyle='--', alpha=0.6, label='Equilibrium Price')\n",
    "\n",
    "ax3.set_title('GMT-II: Price Path Decomposition (Path 1)', fontsize=12, fontweight='bold')\n",
    "ax3.set_xlabel('Time (Years)', fontsize=11)\n",
    "ax3.set_ylabel('Price', fontsize=11)\n",
    "ax3.legend(fontsize=8, loc='upper left')\n",
    "ax3.grid(True, alpha=0.3)\n",
    "\n",
    "# 4. 长记忆性分析 (右下)\n",
    "ax4 = plt.subplot(gs[2, :])\n",
    "if len(gmt_energy_paths) > 0:\n",
    "    # 自相关函数分析\n",
    "    max_lag = 100\n",
    "    autocorrs = []\n",
    "    for lag in range(1, max_lag+1):\n",
    "        corrs = []\n",
    "        for path in gmt_energy_paths:\n",
    "            if len(path) > lag:\n",
    "                corr = np.corrcoef(path[:-lag], path[lag:])[0, 1]\n",
    "                corrs.append(corr)\n",
    "        autocorrs.append(np.mean(corrs))\n",
    "    \n",
    "    # 理论长记忆自相关函数 (Hurst=0.7)\n",
    "    theory_lags = np.arange(1, max_lag+1)\n",
    "    theory_autocorr = 0.5 * ((theory_lags+1)**(2*H) - 2*theory_lags**(2*H) + (theory_lags-1)**(2*H))\n",
    "    \n",
    "    # 自相关图\n",
    "    plt.plot(range(1, max_lag+1), autocorrs, 'bo-', markersize=3, label='Observed Autocorrelation')\n",
    "    plt.plot(theory_lags, theory_autocorr, 'r--', label='Theoretical Autocorrelation (H=0.7)')\n",
    "    plt.axhline(0, color='k', linestyle='-', alpha=0.3)\n",
    "    \n",
    "    # 添加赫斯特指数估算\n",
    "    plt.text(0.7, 0.85, f'Memory Decay Rate: {np.mean(autocorrs[:20]):.4f}/step', \n",
    "             transform=ax4.transAxes, fontsize=9)\n",
    "\n",
    "ax4.set_title('Long-Memory Autocorrelation Analysis', fontsize=12, fontweight='bold')\n",
    "ax4.set_xlabel('Time Lag (steps)', fontsize=11)\n",
    "ax4.set_ylabel('Autocorrelation', fontsize=11)\n",
    "ax4.legend(fontsize=9)\n",
    "ax4.grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('Energy_Price_Long_Memory.png', dpi=300, bbox_inches='tight')\n",
    "\n",
    "# ========================================\n",
    "# GMT-II扩展：添加季节性和尖峰\n",
    "# ========================================\n",
    "print(\"\\nDemonstrating GMT-II Flexibility: Adding Seasonality and Spikes\")\n",
    "\n",
    "class ExtendedEnergyPrice(GeneralizedMappingEnergyPrice):\n",
    "    def __init__(self, P0, mu, kappa, sigma, H, T, dt):\n",
    "        super().__init__(P0, mu, kappa, sigma, H, T, dt)\n",
    "        self.seasonal_factor = [0.0]  # 季节性因子\n",
    "        self.spikes = []              # 尖峰事件记录\n",
    "    \n",
    "    def seasonality_op(self, t):\n",
    "        \"\"\"季节性操作：模拟日/季变化\"\"\"\n",
    "        # 年周期性 (主要季节模式)\n",
    "        annual = 10 * np.sin(2 * np.pi * t)\n",
    "        \n",
    "        # 周周期性 (次要模式)\n",
    "        weekly = 2 * np.sin(8 * np.pi * t)\n",
    "        \n",
    "        seasonal = annual + weekly\n",
    "        self.seasonal_factor.append(seasonal)\n",
    "        return seasonal\n",
    "    \n",
    "    def spike_op(self, t):\n",
    "        \"\"\"尖峰操作：随机出现价格尖峰\"\"\"\n",
    "        # 尖峰概率 (夏季更高)\n",
    "        prob = 0.1 if 0.25 <= (t % 1) <= 0.75 else 0.02\n",
    "        \n",
    "        if np.random.rand() < prob*dt:\n",
    "            # 尖峰大小 (均值为20，标准差5)\n",
    "            spike = np.random.normal(30, 8)\n",
    "            self.spikes.append({'time': t, 'size': spike})\n",
    "            return spike\n",
    "        return 0.0\n",
    "    \n",
    "    def step(self, dt):\n",
    "        \"\"\"重写step方法添加新操作\"\"\"\n",
    "        if self.time_step >= self.n_steps:\n",
    "            return self.P\n",
    "            \n",
    "        t = self.time_step * dt\n",
    "        \n",
    "        # 原有操作\n",
    "        mean_rev = self.mean_revert_op(dt)\n",
    "        fbm_int = self.fbm_integral_op(dt)\n",
    "        \n",
    "        # 新操作\n",
    "        seasonal = self.seasonality_op(t)\n",
    "        spike = self.spike_op(t)\n",
    "        \n",
    "        # 总变化\n",
    "        total_change = mean_rev + fbm_int + seasonal + spike\n",
    "        \n",
    "        # 记录操作细节\n",
    "        self.operations.append({\n",
    "            'time': t,\n",
    "            'mean_reversion': mean_rev,\n",
    "            'fbm_integral': fbm_int,\n",
    "            'seasonality': seasonal,\n",
    "            'spike': spike,\n",
    "            'total_change': total_change\n",
    "        })\n",
    "        \n",
    "        # 更新状态\n",
    "        self.P += total_change\n",
    "        self.path.append(self.P)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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